What are some examples of sampling bias in research?
Sampling bias occurs when certain members of a population are systematically more likely to be selected for a study than others. For example, if a survey about health is conducted only in a gym, it may not accurately represent the general population's health.
Can you give me another example?
Sure! If a researcher studies the effects of a new drug by only including participants from a specific age group, they may miss how the drug affects other age groups, leading to biased results.
How can researchers avoid sampling bias?
Researchers can avoid sampling bias by using random sampling methods, ensuring that every individual in the population has an equal chance of being selected.
What are the consequences of sampling bias?
The consequences can include inaccurate conclusions, misrepresentation of the population, and ultimately, ineffective policies or treatments based on flawed data.
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